1. Field
The present application relates to machine learning systems, and, more particularly, to using split machine learning systems to generate an output for an input.
2. Related Art
Machine learning systems have been used in a variety of applications. Typically, a machine learning system is configured to receive an input and generate an output for the received input using a learned relationship. The machine learning system maps, via the learned relationship, received members of an input set to members of an output set. In some cases, the input set may be viewed as a domain of a function and the output set may be viewed as a range of the function, where the function is the learned relationship.
When the input set is relatively small and uncomplicated, a single machine learning system may be efficiently trained on the learned relationship to accurately map each member of the input set to a member of the output set. However, as the size and complexity of the input set increases, the training time required for the single machine learning system also increases. Additionally, a large and complex input set can result in a poorly trained machine learning system.